A new framework integrates graph databases with real-time machine learning to enhance fraud detection and risk control in digital finance. By ...
BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...
Read more about New AI model revolutionizes urban water infrastructure with real-time forecasting on Devdiscourse ...
Gibaldi and his colleagues have since analysed several open-access MOF databases commonly used for machine learning and found ...
Unmanned Swarm Systems (USS) have transformed key fields like disaster rescue, transportation, and military operations via distributed coordination, yet trajectory prediction accuracy and interaction ...
Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
Graph database provider Neo4j Inc. today announced that it will invest $100 million to accelerate its role as what it calls the “default knowledge layer” for agentic systems and generative artificial ...
An initial step of most NMR studies is identifying peaks in the obtained spectrum. Producing a peak list is especially crucial if the spectrum is automatically prepared. Peak picking is still ...
A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...
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